devrelopers

devrelopers / hackernews-mcp

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A Rust MCP server exposing Hacker News to AI assistants over stdio. Read the front page and Ask/Show/job stories, walk full comment trees with depth control, fetch user profiles, and run full-text search. Backed by the official Firebase and Algolia APIs — no keys, no auth.

crates.iocrateshackernews-mcp
10
0
100% credibility
Found May 31, 2026 at 10 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Rust
AI Summary

This is a helpful tool that lets AI assistants like Claude Desktop and Claude Code access Hacker News content. It provides four simple ways to explore HN: browse ranked story feeds (top, new, best, ask, show, job), read individual stories with their full comment threads, search all of HN by keyword, and look up user profiles. The tool connects to two public Hacker News databases that anyone can access—no special accounts or keys needed. Everything is read-only, so nothing can be posted or changed. The tool is designed to be polite to the HN servers by limiting how many requests it makes at once, and it carefully caps comment trees so your AI assistant's context window doesn't get overwhelmed. It's MIT licensed and open source.

How It Works

1
💡 You want to explore Hacker News

You discover that your AI assistant can help you browse stories, search discussions, and look up users on Hacker News without opening a browser.

2
🔧 You connect the tool to your assistant

You add this little helper to your AI assistant's configuration so it knows how to talk to Hacker News.

3
✨ Everything springs to life

Your AI assistant now has four superpowers: browse the front page, read full discussions with replies, search by keyword, and look up any user's profile.

4
You choose your adventure
📰
Browse the feeds

Scan top stories, newest posts, best discussions, or specialized sections like Ask HN or Show HN.

🔍
Search for topics

Find stories and comments about anything you're curious about, sorted by relevance or date.

💬
Read a discussion in depth

Dive into a specific thread and read through the nested conversation, with replies neatly organized.

👤
Look up someone

Check out a user's profile, see their karma, when they joined, and how much they've contributed.

🎉 You get exactly what you needed

Whether it's staying informed, researching a topic, or following a conversation, your AI assistant delivers the HN content you wanted in a clean, easy-to-read format.

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AI-Generated Review

What is hackernews-mcp?

This is a Rust-based MCP server that gives AI assistants like Claude Desktop and Claude Code direct access to Hacker News. It speaks over stdio using the Model Context Protocol and connects to two public HN APIs — the official Firebase endpoint and Algolia search — without requiring any API keys or authentication. You get four tools: browse ranked feeds, read individual threads with nested comment trees, look up user profiles, and run full-text search across all of HN. The comment tree walker is breadth-first and hard-capped by depth and total count to keep responses manageable for LLM context windows.

Why is it gaining traction?

The no-auth, no-keys setup is the hook — it works out of the box. Developers building AI-powered workflows around Hacker News can wire this up in minutes rather than wrangling Firebase credentials or rate limits. The concurrent fetching with a polite concurrency cap means you get fast bulk reads without hammering the upstream APIs. The truncation logic on comment trees is thoughtful: it tells you when and why replies were cut, so the AI knows the response is partial rather than silently dropping content.

Who should use this?

AI developers building Claude-powered tools that need live HN data will find this immediately useful. Researchers monitoring HN for trends, writers curating content, or anyone tired of scraping the site manually can plug this into Claude Code for natural-language HN queries. It's less useful if you need write access or real-time push notifications — this is strictly read-only.

Verdict

At 10 stars with minimal test coverage visible, this is an early-stage project that solves a real problem but carries the usual "v0.1" maturity risks. The 1.0% credibility score reflects that low visibility. Worth trying if you want frictionless HN access in your AI workflows, but audit the error handling before trusting it in production.

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